diff --git a/ci/.travis_install.sh b/ci/.travis_install.sh
index 267d8e601..b3adb8237 100755
--- a/ci/.travis_install.sh
+++ b/ci/.travis_install.sh
@@ -53,6 +53,8 @@ fi
 
 pip install update_checker
 pip install tqdm
+pip install scikit-mdr
+pip install skrebate
 
 if [[ "$COVERAGE" == "true" ]]; then
     pip install coverage coveralls
diff --git a/tests.py b/tests.py
index 21163100d..788cb6654 100644
--- a/tests.py
+++ b/tests.py
@@ -40,7 +40,7 @@
 from datetime import datetime
 import subprocess
 
-from sklearn.datasets import load_digits, load_boston
+from sklearn.datasets import load_digits, load_boston, make_classification
 from sklearn.model_selection import train_test_split, cross_val_score
 from deap import creator
 from tqdm import tqdm
@@ -175,7 +175,7 @@ def test_set_params_2():
 
     assert tpot_obj.generations == 3
 
-def test_lite_params():
+def test_config_dict_params():
     """Assert that TPOT uses TPOT's lite dictionary of operators when config_dict is \'TPOT light\' or \'TPOT MDR\'"""
     tpot_obj = TPOTClassifier(config_dict='TPOT light')
     assert tpot_obj.config_dict == classifier_config_dict_light
@@ -426,6 +426,7 @@ def test_warm_start():
 
     assert tpot_obj._pop == first_pop
 
+
 def test_fit():
     """Assert that the TPOT fit function provides an optimized pipeline"""
     tpot_obj = TPOTClassifier(random_state=42, population_size=1, offspring_size=2, generations=1, verbosity=0)
@@ -434,6 +435,7 @@ def test_fit():
     assert isinstance(tpot_obj._optimized_pipeline, creator.Individual)
     assert not (tpot_obj._start_datetime is None)
 
+
 def test_fit2():
     """Assert that the TPOT fit function provides an optimized pipeline when config_dict is \'TPOT light\'"""
     tpot_obj = TPOTClassifier(random_state=42, population_size=1, offspring_size=2, generations=1, verbosity=0, config_dict='TPOT light')
@@ -442,6 +444,17 @@ def test_fit2():
     assert isinstance(tpot_obj._optimized_pipeline, creator.Individual)
     assert not (tpot_obj._start_datetime is None)
 
+
+def test_fit3():
+    """Assert that the TPOT fit function provides an optimized pipeline when config_dict is \'TPOT MDR\'"""
+    X, y = make_classification(n_samples=50, n_features=10, random_state=42, n_classes=2) # binary classification problem
+    tpot_obj = TPOTClassifier(random_state=42, population_size=1, offspring_size=2, generations=1, verbosity=0, config_dict='TPOT MDR')
+    tpot_obj.fit(X, y)
+
+    assert isinstance(tpot_obj._optimized_pipeline, creator.Individual)
+    assert not (tpot_obj._start_datetime is None)
+
+
 def testTPOTOperatorClassFactory():
     """Assert that the TPOT operators class factory"""
     test_config_dict = {
diff --git a/tpot/config_classifier_mdr.py b/tpot/config_classifier_mdr.py
index a90a9a702..402a066d9 100644
--- a/tpot/config_classifier_mdr.py
+++ b/tpot/config_classifier_mdr.py
@@ -30,7 +30,7 @@
 
     # Classifiers
 
-    'mdr.MDR': {
+    'mdr.MDRClassifier': {
         'tie_break': [0, 1],
         'default_label': [0, 1]
     },